The monitoring or evaluation of film or video content is an area of growing interest, both for broadcasters and content owner or content management organizations.
In particular, it is desirable for broadcast organizations to be able to monitor the audio-visual content being broadcast to identify, and therefore quickly respond to, problems or errors in the broadcast chain, for example the picture becoming all-black. Typically, previously this has been achieved by a person visually monitoring the program output, or more generally monitoring a number of program outputs, and visually identifying errors in the program output. Clearly this is personnel-intensive and it is desirable to provide automated or semi-automated monitoring and error detection.
In addition, it is increasingly desirable for content owner/management organizations to be able to analyse content and to generate metadata that describes aspects of the content. One example of this technique might be to analyse content to determine the presence of all-black frames and create associated metadata.
One application in which this might be useful is the automated or semi-automated monitoring and error detection as outlined above. Thus, black frames identified in the accompanying metadata are not considered as “errors” on playout of a program content, and only black frames arising from genuine errors, instead of from the program material, give rise to an alarm. This enhances the reliability of the monitoring and error detection.